Data Architect Lisboa

Data Architect
Lisboa
Lisboa, Lisboa, Portugal

Boost IT is made up of people who are motivated to improve the world and who are passionate about technology. Our vision focuses on the skill to bring people together around complex
- solving for our clients, creating sophisticated solutions.

People are our most important asset and the reason for our business. We are proud of our strong culture, which challenges the status quo and always searches for the best solution for our clients. We believe technology can lead to a positive change in society, connect and inspire, and, ultimately, lead to a better future.

ROLE: Data Architect

Deliverables:

• Deliver
  - defined conceptual, logical, and physical data models for the domain, ensuring they align with both business requirements and the broader enterprise architecture
• Deliver a clear roadmap for data adoption and compliance with the ADEO Data Catalog.
• Ensure the delivery of understood and reusable data assets to the platform that support digital product teams

Technical Skills:

• Data Architecture & Modeling - Competent - Required
• Conceptual Model & Roadmap Development - Competent - Required
• Data modeling tools - Competent - Important
• Big
  Query - Competent - Important

Role Overview:

The Data Architect is responsible for designing and overseeing the data models within a specific business domain. This role plays a critical part in contributing to the target Enterprise Architecture by designing the data layer in alignment with business goals and digital strategies. The Data Architect ensures that the domain's data is compliant with enterprise data management standards, supports platform needs, and drives the adoption of a data mesh approach across the organization. The role also focuses on reducing data debt and delivering
- quality,
- understood data assets.

Tools & Technologies:

Collibra: For data governance, quality, and cataloging.

Google Cloud Platform (GCP): Expertise in Big
Query, Data
Flow, Pub/Sub, etc.

Data Mesh: Applied understanding of decentralized data ownership models.

Data Modeling Tools: Experience with tools like ER/Studio, ERwin, or similar.